Advice on how to land GPU/ML Systems interviews [D]

Hi, I’m a recent MS in Data Science grad seeking entry-level GPU/ML Systems or Inference Engineering roles. (Currently on F1 OPT).

Background: CUDA, Metal, and Triton work - built a FlashAttention kernel in Metal for Apple Silicon (tiled, online softmax, fp16 with simdgroup matrix intrinsics), a distributed Mixture-of-Experts layer using NCCL alltoall for expert-parallel token dispatch with a custom Triton kernel, and various CUDA kernels using shared memory tiling and warp-level primitives.

Experience: Worked at a FinTech for a year then came to the US for Master’s. No job experience as a HPC engineer.

Few things I'd appreciate help with:

1. Any advice on what technical interview loops for these roles actually emphasize right now - I've heard mixed things about how much weight standard Leetcode carries versus systems/kernel-writing rounds.
2. ⁠I’ve only heard back from one company yet - Apple (made it to the second screen). If you have any advice for me or tips for my resume, please let me know.
3. Should I target startups for AI inference/infra roles first, or keep pushing for kernel-level roles at bigger companies?

Happy to share more details if useful. Thanks for reading. If anyone is looking for similar roles or is in a similar situation, I’d like to connect with you, feel free to DM me!

https://preview.redd.it/smnp7vboqhfh1.png?width=1162&format=png&auto=webp&s=79d0d28825c8b137f8889ef7d84d299bf0ac2d0f